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Diagnosis. I. Symptom nonindependence in mathematical models for diagnosis
dc.contributor.authorNorusis, Marija J.en_US
dc.contributor.authorJacquez, John A.en_US
dc.date.accessioned2006-04-07T16:38:13Z
dc.date.available2006-04-07T16:38:13Z
dc.date.issued1975-04en_US
dc.identifier.citationNorusis, Marija J., Jacquez, John A. (1975/04)."Diagnosis. I. Symptom nonindependence in mathematical models for diagnosis." Computers and Biomedical Research 8(2): 156-172. <http://hdl.handle.net/2027.42/22081>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6WCY-49TJVKT-JW/2/3b62978e624cf2b4919a4724882a7678en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/22081
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=1091409&dopt=citationen_US
dc.description.abstractThe consequences of the simplifying assumption of independence of symptoms are examined by considering a data base of cardiovascular disease patients. A mathematical model based on Bahadur's expansion (16) is used for quantification of nonindependence. It is shown that small symptom dependencies are sufficient to cause a substantial increase over the minimum misclassification rate. Incorporation of symptom interactions by use of Fisher's linear discriminant function, optimum tree dependence models (21), and Bahadur's expansion is also discussed.en_US
dc.format.extent1059946 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleDiagnosis. I. Symptom nonindependence in mathematical models for diagnosisen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelPublic Healthen_US
dc.subject.hlbsecondlevelWest European Studiesen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.subject.hlbtoplevelHumanitiesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumUniversity of Chicago Pritzker School of Medicine, Chicago, Illinois 60637, USA: University of Michigan School of Public Health, Ann Arbor, Michigan 48104, USA: The Medical School, Ann Arbor, Michigan 48104, USAen_US
dc.contributor.affiliationumUniversity of Chicago Pritzker School of Medicine, Chicago, Illinois 60637, USA: University of Michigan School of Public Health, Ann Arbor, Michigan 48104, USA: The Medical School, Ann Arbor, Michigan 48104, USAen_US
dc.identifier.pmid1091409en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/22081/1/0000505.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0010-4809(75)90036-1en_US
dc.identifier.sourceComputers and Biomedical Researchen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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